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In laser powder bed fusion (LPBF) additive manufacturing, melt pool characterization is one of the potential approaches toward rapid process qualification and efficient non-destructive evaluation of printed parts. Especially melt pool width measurement is crucial for understanding the print process regimes, estimating the solidified melt pool depth, and identifying any process anomalies, among other attributes of interest. While existing works focus on monitoring melt pools of single scan tracks or single layer prints, melt pool characterization for a multi-track multi-layer (MTML) LPBF print has not been extensively studied. In this work, we employ our lab-designed coaxial single-camera two-wavelength imaging pyrometry (STWIP) system to monitor in-situ melt pool properties during a MTML LPBF process. The STWIP-measured melt pool widths are validated using a serial sectioning machine (Robo-Met, UES). The in-situ STWIP and ex-situ Robo-Met measurement data are in close agreement with each other, having a mean absolute error and root mean squared error of 9.83 μm and 16.53 μm, respectively. Furthermore, we demonstrate the successful mapping of melt pool location and melt pool size on the printed MTML part. In sum, this work demonstrates the capability and the applicability of STWIP for accurate large-scale melt pool monitoring during LPBF processing of practical parts, thereby facilitating the development of LPBF process models and control strategies. [ABSTRACT FROM AUTHOR]

• Established comprehensive framework of fringe projection profilometry (FPP) for LPBF-AM. • Enhanced FPP measurement performance in the application scenario of LPBF. • Improved phase wrapping and unwrapping by pixel-wise correction and applying DFT. • Comprehensive measurement uncertainty calculations for the LPBF-specific FPP. • Quantitative comparison & validation of FPP measurement against standard equipment. Fringe Projection Profilometry (FPP) is a cost-effective and non-invasive technology that has been shown to measure finer features. In this work, we developed an in-situ FPP method to measure the dynamic topography of powder bed and printed layer during Laser Powder Bed Fusion (LPBF) additive manufacturing (AM) process. A systematic study towards developing a comprehensive framework of LPBF-specific FPP is demonstrated to enhance and evaluate the performance of applying FPP for in-situ LPBF monitoring, including 1) a modified sensor model with localized correction; 2) improved phase unwrapping with FFT filtering 3) quantitative uncertainty analysis; and 4) experimental validation with ex-situ characterization. The developed LPBF-specific FPP system and methods are implemented on a commercial LPBF-AM machine, achieving better accuracy, more robustness, and increased field of view while maintaining sufficient measurement range and decent resolution, in contrast to literature methods. The established FPP framework will facilitate the development of closed-loop control strategies for advancing LPBF based AM. [ABSTRACT FROM AUTHOR]

This paper details the design and operation of a testbed to evaluate the concept of autonomous manufacturing to achieve a desired manufactured part performance specification. This testbed, the autonomous manufacturing system for phononic crystals (AMSPnC), is composed of additive manufacturing, material transport, ultrasonic testing, and cognition subsystems. Critically, the AMSPnC exhibits common manufacturing deficiencies such as process operating window limits, process uncertainty, and probabilistic failure. A case study illustrates the AMSPnC function using a standard supervised learning model trained by printing and testing an array of 48 unique designs that span the allowable design space. Using this model, three separate performance specifications are defined and an optimization algorithm is applied to autonomously select three corresponding design sets to achieve the specified performance. Validation manufacturing and testing confirms that two of the three optimal designs, as defined by an objective function, achieve the desired performance, with the third being outside the design window in which a distinct bandpass is achieved in phononic crystals (PnCs). Furthermore, across all samples, there is a marked difference between the observed bandpass characteristics and predictions from finite elements method computation, highlighting the importance of autonomous manufacturing for complex manufacturing objectives. [ABSTRACT FROM AUTHOR]